most citedRecent Developments in GNNs for Drug Discovery

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025★ 2 cited

Recent Developments in GNNs for Drug Discovery

Zhengyu Fang, Xiaoge Zhang, Anyin Zhao +3

In this paper, we review recent developments and the role of Graph Neural Networks (GNNs) in computational drug discovery, including molecule generation, molecular property predict…

cs.LG2025

A Closer Look on Memorization in Tabular Diffusion Model: A Data-Centric Perspective

Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen +4

Diffusion models have shown strong performance in generating high-quality tabular data, but they carry privacy risks by reproducing exact training samples. While prior work focuses…

cs.LG2025★ 1 cited

Dual-Modality Representation Learning for Molecular Property Prediction

Anyin Zhao, Zuquan Chen, Zhengyu Fang +2

Molecular property prediction has attracted substantial attention recently. Accurate prediction of drug properties relies heavily on effective molecular representations. The struct…

cs.LG2024

Understanding and Mitigating Memorization in Diffusion Models for Tabular Data

Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen +2

Tabular data generation has attracted significant research interest in recent years, with the tabular diffusion models greatly improving the quality of synthetic data. However, whi…

cs.CL2024

Detection of Opioid Users from Reddit Posts via an Attention-based Bidirectional Recurrent Neural Network

Yuchen Wang, Zhengyu Fang, Wei Du +3

The opioid epidemic, referring to the growing hospitalizations and deaths because of overdose of opioid usage and addiction, has become a severe health problem in the United States…